scholarly journals Investigation of the Influence of the Parameters of the VFH + Method on the Navigation Efficiency of the Mobile Robot

2021 ◽  
Vol 16 ◽  
pp. 328-334
Author(s):  
Andrej Šutý ◽  
František Duchoň
Keyword(s):  
Mobile Robot ◽  
Robot Navigation ◽  
Robot Dynamics ◽  
Simulation Environment ◽  
Criterion Function ◽  
Reactive Navigation ◽  
The Impact ◽  
Navigation Method

The article focuses on verifying the effects of the VFH + navigation method parameters, proving to be very effective for the robot's reactive navigation. This research is based on our long-standing knowledge of histogram methods used in robot navigation. The article focuses on verifying the influence of crucial parameters - thresholds in a binary histogram, the smax parameter defining wide and narrow valleys, constants setting the criterion function, and the impact of robot dynamics on navigation. Many experiments were performed in a ROS simulation environment, and the article lists those significant confirming certain assumptions in setting these parameters.

scholarly journals Multi-Focal Vision and Gaze Control Improve Navigation Performance

10.5772/50920 ◽  
2012 ◽  
Vol 9 (1) ◽  
pp. 25 ◽  
Author(s):  
Kolja Kühnlenz ◽  
Martin Buss
Keyword(s):  
Mobile Robot ◽  
Robot Navigation ◽  
Active Vision ◽  
Path Following ◽  
Mobile Robot Navigation ◽  
Vision Systems ◽  
Localization Accuracy ◽  
Localization And Mapping ◽  
Novel Concept ◽  
The Impact

Multi-focal vision systems comprise cameras with various fields of view and measurement accuracies. This article presents a multi-focal approach to localization and mapping of mobile robots with active vision. An implementation of the novel concept is done considering a humanoid robot navigation scenario where the robot is visually guided through a structured environment with several landmarks. Various embodiments of multi-focal vision systems are investigated and the impact on navigation performance is evaluated in comparison to a conventional mono-focal stereo set-up. The comparative studies clearly show the benefits of multi-focal vision for mobile robot navigation: flexibility to assign the different available sensors optimally in each situation, enhancement of the visible field, higher localization accuracy, and, thus, better task performance, i.e. path following behavior of the mobile robot. It is shown that multi-focal vision may strongly improve navigation performance.

A Novel Mobile Robot Navigation Method Based on Hand-Drawn Paths

2020 ◽  
Vol 20 (19) ◽  
pp. 11660-11673
Author(s):  
Xuyan Hou ◽  
Wei Li ◽  
Yuexing Han ◽  
Aoxiang Wang ◽  
Yihui Yang ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Robot Navigation ◽  
Mobile Robot Navigation ◽  
Navigation Method

scholarly journals Mobile Robot Navigation Based on Circle Recognition

2013 ◽  
Vol 64 (2) ◽  
pp. 84-91 ◽  
Author(s):  
Peter Pásztó ◽  
Peter Hubinský
Keyword(s):  
Image Processing ◽  
Visual System ◽  
Mobile Robot ◽  
Trajectory Planning ◽  
Relative Position ◽  
Robot Navigation ◽  
Recognition Task ◽  
Mobile Robot Navigation ◽  
Planning Algorithm ◽  
Navigation Method

This paper presents a navigation method for a mobile robot using a visual system. Circular marks with specific colors are used for marking the significant points of the mobile robot’s trajectory that it needs to pass. The colors of the used marks are signalizing the way of their bypassing with the mobile robot (from the left or right side). The mobile robot uses only one camera for the marks recognition task and it is able to determine its own relative position from the detected marks. The image processing and the mobile robot’s trajectory planning algorithm working in real-time are described in this paper.

scholarly journals An Artificial Potential Field Based Mobile Robot Navigation Method To Prevent From Deadlock

2015 ◽  
Vol 5 (3) ◽  
pp. 189-203 ◽  
Author(s):  
Tharindu Weerakoon ◽  
Kazuo Ishii ◽  
Amir Ali Forough Nassiraei
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Robot Navigation ◽  
Mobile Robot Navigation ◽  
Front Face ◽  
Local Minima ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Navigation Method ◽  
Robot Path

Abstract Artificial Potential Filed (APF) is the most well-known method that is used in mobile robot path planning, however, the shortcoming is that the local minima. To overcome this issue, we present a deadlock free APF based path planning algorithm for mobile robot navigation. The Proposed-APF (P-APF) algorithm searches the goal point in unknown 2D environments. This method is capable of escaping from deadlock and non-reachability problems of mobile robot navigation. In this method, the effective front-face obstacle information associated with the velocity direction is used to modify the Traditional APF (T-APF) algorithm. This modification solves the deadlock problem that the T-APF algorithm often converges to local minima. The proposed algorithm is explained in details and to show the effectiveness of the proposed approach, the simulation experiments were carried out in the MATLAB environment. Furthermore, the numerical analysis of the proposed approach is given to prove a deadlock free motion of the mobile robot.

scholarly journals Indoor Vision/INS Integrated Mobile Robot Navigation Using Multimodel-Based Multifrequency Kalman Filter

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yuan Xu ◽  
Tongqian Liu ◽  
Bin Sun ◽  
Yong Zhang ◽  
Siamak Khatibi ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Mobile Robot ◽  
Navigation System ◽  
Robot Navigation ◽  
Visual Navigation ◽  
Mobile Robot Navigation ◽  
Integrated Navigation ◽  
Position Information ◽  
Integrated Navigation System ◽  
Navigation Method

In order to further improve positioning accuracy, this paper proposes an indoor vision/INS integrated mobile robot navigation method using multimodel-based multifrequency Kalman filter. Firstly, to overcome the insufficient accuracy of visual data when a robot turns, a novel multimodel integrated scheme has been investigated for the mobile robots with Mecanum wheels which can make fixed point angled turns. Secondly, a multifrequency Kalman filter has been used to fuse the position information from both the inertial navigation system and the visual navigation system, which overcomes the problem that the filtering period of the integrated navigation system is too long. The proposed multimodel multifrequency Kalman filter gives the root mean square error (RMSE) of 0.0184 m in the direction of east and 0.0977 m in north, respectively. The RMSE of visual navigation system is 0.8925 m in the direction of east and 0.9539 m in north, respectively. Experimental results show that the proposed method is effective.

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